Knowledge representation for grounded theory construction in qualitative data analysis

The major achievement of most current qualitative data analysis software systems in social sciences has been the efficient code‐and‐retrieve abilities. Although such abilities greatly strengthen and assist the handling of qualitative data, they do not address the crucial tasks of theory construction as traditionally understood in qualitative research. Application of knowledge‐based systems has been recognised as an important approach to theory construction in qualitative data analysis. This approach heavily depends on a suitable way of knowledge representatioa This paper describes a knowledge representation method for representing grounded theory construction, in which a hybrid approach of fuzzy set theory and semantic networks is applied.

[1]  Lyn Richards,et al.  Computing in Qualitative Analysis: A Healthy Development? , 1991 .

[2]  Roberto Franzosi,et al.  Computer-Assisted Coding of Textual Data , 1990 .

[3]  Willard Van Orman Quine,et al.  From a Logical Point of View , 1955 .

[4]  Anselm L. Strauss,et al.  Qualitative Analysis For Social Scientists , 1987 .

[5]  A. Strauss,et al.  The Discovery of Grounded Theory , 1967 .

[6]  David Harel,et al.  On visual formalisms , 1988, CACM.

[7]  Bo Anderson On artificial intelligence and theory construction in sociology , 1989 .

[8]  Ronald E. Anderson,et al.  Computer applications in the social sciences , 1990 .

[9]  P. G. Reddy,et al.  Implementation of Conceptual Graphs using Frames in LEAD , 1989, KBCS.

[10]  Steven J. Taylor Introduction to qualitative research methods , 1975 .

[11]  Marvin Minsky,et al.  A framework for representing knowledge , 1974 .

[12]  Paul Dupuis,et al.  HyperRESEARCH: A computer program for the analysis of qualitative data with an emphasis on hypothesis testing and multimedia analysis , 1991 .

[13]  J. Turner,et al.  社会学理论的结构 = The Structure of Sociological Theory , 1975 .

[14]  Antonio M. Lopez,et al.  A Frame-based design for the TIMS and CAMS metadata for a stennis information management system , 1993, J. Syst. Softw..

[15]  T. Richards,et al.  The NUDIST qualitative data analysis system , 1991 .

[16]  P. Johnson-Laird Mental models , 1989 .

[17]  Renata Tesch,et al.  Qualitative research : analysis types and software tools , 1990 .

[18]  August H. Mason,et al.  Writing and Thinking , 1932 .

[19]  Günter L. Huber,et al.  Computer assistance for testing hypotheses about qualitative data: The software package AQUAD 3.0 , 1991 .

[20]  Didier Dubois,et al.  Fuzzy sets and systems ' . Theory and applications , 2007 .

[21]  Kathleen M. Carley Formalizing the Social Expert's Knowledge , 1988 .

[22]  Henry Teune,et al.  A Rationalist Methodology for the Social Sciences , 1985 .

[23]  A. Bryman Quantity and quality in social research , 1988 .

[24]  T. Muhr ATLAS/ti — A prototype for the support of text interpretation , 1991 .

[25]  W. Quine,et al.  The web of belief , 1970 .

[26]  Michael Smithson,et al.  Applications of fuzzy set concepts to behavioral sciences , 1982, Math. Soc. Sci..

[27]  Kathleen M. Carley,et al.  Extracting, Representing, and Analyzing Mental Models , 1992 .

[28]  John T. Nosek,et al.  A Comparison of Formal Knowledge Representation Schemes as Communication Tools: Predicate Logic vs Semantic Network , 1990, Int. J. Man Mach. Stud..

[29]  James Lyle Peterson,et al.  Petri net theory and the modeling of systems , 1981 .

[30]  Michael Smithson,et al.  A new dimension to content analysis: Exploring relationships among thematic categories , 1987 .

[31]  Edward Brent Is there a role for artificial intelligence in sociological theorizing? , 1988 .

[32]  A. Strauss Basics Of Qualitative Research , 1992 .

[33]  Roy Rada Hypertext: from Text to Expertext , 1994, SIGB.

[34]  A. Sayer Method in Social Science , 1992 .

[35]  R. Tesch Qualitative Research: Analysis Types and Software , 1990 .